English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

One of the most important tasks in the characterization of unconventional tight-gas sandstone reservoirs is a proper evaluation of rock types (RT). Rock typing based on pore structure has a great potential to capture fluctuations in storage potential, and fluid transport within the formations studied. This study presents a newly adapted workflow to formulate rock types in tight-gas sandstone reservoirs based on similarities in pore structure. Rock types are identified using the k-means clustering method (unsupervised learning) on pore structure parameters derived from measuring mercury injection capillary pressure (MICP). The parameters associate opened porosity, proportions of macro-, meso-, micro-, and nanopores, and selected MICP-derived permeability. The correlation between pulse decay permeability and permeabilities calculated from MICP analysis revealed that Swanson permeability is the most useful permeability estimation for rock typing. The cluster analysis performed on 178 samples revealed four rock types (RT1–RT4) of unique pore system characteristics that significantly differ in macro-, meso-, micro-, and nanopore content. The clusters’ tendency was evaluated using the Hopkins statistic. The optimal number of clusters was determined using the Elbow method as an internal validation technique. Rock types 1 and 2 (RT1 and RT2) showed a highly tight character with a Swanson permeability of < 0.1 mD and an opened porosity of < 5%. Samples from RT3 and RT4 revealed more conventional characteristics with a Swanson permeability of > 0.1 mD and an opened porosity of > 5%. The variability in the pore structure between designated rock types was also captured using Computerized Analysis of Microscopic Images (CAMI) on the thin-sections from the most representative samples of the individual rock types. Pore structure characteristics (opened porosity and pore-throat distribution) with Swanson permeability and rock types were integrated into an array log to locate the most perspective intervals within the formation under study.

An integrated workflow for MICP-based rock typing: A case study of a tight-gas sandstone reservoir in the Baltic Basin (Poland)